Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Milde M. S. Lira"'
Autor:
Jonata C. de Albuquerque, Ronaldo R. B. de Aquino, Otoni Nobrega Neto, Milde M. S. Lira, Aida A. Ferreira, Manoel Afonso de Carvalho
Publikováno v:
Journal of Modern Power Systems and Clean Energy, Vol 9, Iss 3, Pp 526-533 (2021)
We propose a new way to develop non-parametric models of power curves using artificial intelligence tools. One parametric model and eight non-parametric models are developed to emulate the behavior described by the power curve of the wind farms. A co
Externí odkaz:
https://doaj.org/article/ccb465667c174fc7b78379814b929509
Autor:
Ronaldo R. B. de Aquino, Milde M. S. Lira, Jonata C. de Albuquerque, Aida A. Ferreira, Otoni Nobrega Neto, Manoel A. Carvalho
Publikováno v:
Journal of Modern Power Systems and Clean Energy, Vol 9, Iss 3, Pp 526-533 (2021)
This paper proposes a new way of developing non-parametric models of power curves, using artificial intelligence tools. Here, nine models are developed, one being parametric and eight non-parametric, to emulate the behavior dictated by the power curv
Publikováno v:
Revista Cartográfica. :13-31
En las últimas décadas, el crecimiento de las urbanizaciones viene provocado grandes transformaciones en los aspectos sociales, económicos y morfológicos en las áreas costeras. Las playas urbanas de Boa Viagem y Pina (Recife-PE) y la playa de Pi
Publikováno v:
Revista Cartográfica, Iss 96 (2018)
Nas últimas décadas, o crescimento da urbanização vem provocando grandes transformações nos aspectos sociais, econômicos e morfológicos nas áreas costeiras. As praias urbanas de Boa Viagem e Pina (Recife-PE) e a praia de Piedade (Jaboatão d
Publikováno v:
Electrical Engineering. 100:1317-1325
Dissolved gas analysis of insulating oil in refrigerated power transformer oil is a widespread technique for detecting incipient faults. However, this technique involves safety procedures for the collection of oil samples, laboratory response times a
Autor:
Aida A. Ferreira, Alcides Codeceira Neto, Milde M. S. Lira, Ronaldo R. B. de Aquino, Otoni Nobrega Neto, Jonata C. de Albuquerque
Publikováno v:
2017 International Conference on Computational Science and Computational Intelligence (CSCI).
This paper, proposes the use of Deep Learning in predictive nonparametric models that use artificial intelligence tools to approximate power curves of wind farms. Three different tools are evaluated: artificial neural networks, fuzzy inference system
Autor:
Agnaldo Magnum, Heldemarcio Ferreira, Milde M. S. Lira, Viviane K. Asfora, Ronaldo Ribeiro Barbosa de Aquino, Taciana Filgueiras
Publikováno v:
Anais do 9. Congresso Brasileiro de Redes Neurais.
Autor:
Manoel Firmino de Medeiros, José Tavares de Oliveira, Milde M. S. Lira, José Júlio A. L. Leitão, Adriao Duarte Doria Neto, Crisluci K. S. Santos, Paulo S. da M. Pires, Jorge Dantas de Melo
Publikováno v:
Anais do 7. Congresso Brasileiro de Redes Neurais.
Autor:
José Júlio A. L. Leitão, Mêuser J. S. Valença, Milde M. S. Lira, Ronaldo Ribeiro Barbosa de Aquino, Manoel Afonso De Carvalho Junior
Publikováno v:
Anais do 7. Congresso Brasileiro de Redes Neurais.
Autor:
Aida A. Ferreira, Manoel A. Carvalho, Otoni Nobrega Neto, Jonata C. de Albuquerque, Alcides Codeceira Neto, Ronaldo R. B. de Aquino, Milde M. S. Lira
Publikováno v:
IJCNN
The modeling of wind power curve is important in turbine performance monitoring and in wind power forecasting. There are several techniques to fit the power curve of a wind turbine, which can be classified into parametric and nonparametric methods. T